steadyICA (version 1.0)

whitener: Whitening function

Description

Subtract column means and transform columns such that the empirical covariance is equal to the identity matrix. Uses the SVD.

Usage

whitener(X, n.comp = ncol(X), center.row = FALSE, irlba = FALSE)

Arguments

X

n x p matrix

n.comp

number of components to retain, i.e., first n.comp left eigenvectors from svd are retained

center.row

center both rows and columns prior to applying SVD (the resulting whitened data does not have zero-mean rows)

irlba

if TRUE, uses irlba to approximate the first n.comp left eigenvectors. See Note.

Value

• whitener
  the matrix such that X%*%whitener has zero mean and covariance equal to the identity matrix
• Z
  the whitened data, i.e., X%*%whitener = Z

See Also

svd, irlba::irlba

Examples

simData <- cbind(rnorm(1000,1,2),rnorm(1000,-1,3),rnorm(1000,4,1))
simMVN <- simData%*%matrix(rnorm(12),3,4)
simWhiten <- whitener(simMVN,n.comp = 3)
colMeans(simWhiten$Z)
cov(simWhiten$Z)